COMP SCI 2103 - Algorithm Design & Data Structures

North Terrace Campus - Semester 1 - 2020

The course is structured to take students from an introductory knowledge of C++ to a higher level, as well as addressing some key areas of computer programming and algorithm design. Topics include: abstract data types, class hierarchies, inheritance, friends, polymorphism and type systems; OO design principles, testing and software reuse; algorithmic strategies and introductory complexity analysis; recursion, linked lists, stacks, queues and trees.

  • General Course Information
    Course Details
    Course Code COMP SCI 2103
    Course Algorithm Design & Data Structures
    Coordinating Unit School of Computer Science
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites COMP SCI 1009, COMP SCI 1102 or COMP SCI 1202
    Incompatible COMP SCI 1103, COMP SCI 1203, COMP SCI 2004, COMP SCI 2202, COMP SCI 2202B
    Course Description The course is structured to take students from an introductory knowledge of C++ to a higher level, as well as addressing some key areas of computer programming and algorithm design. Topics include: abstract data types, class hierarchies, inheritance, friends, polymorphism and type systems; OO design principles, testing and software reuse; algorithmic strategies and introductory complexity analysis; recursion, linked lists, stacks, queues and trees.
    Course Staff

    Course Coordinator: Professor Frank Neumann

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

    1 Program in C/C++ in the OO paradigm,
    2 Manage memory usage in C/C++ programs,
    3 Explain fundamental computing algorithms,
    4 Analyse algorithms and identify key algorithmic strategies,
    5 Demonstrate familiarity with fundamental software engineering practices,
    6 Demonstrate knowledge of programming language design issues,
    7 Demonstrate professional writing skills at an introductory level.
    8 Demonstrate knowledge of ethical concepts in the context of software production.
    9 Work competently in a group to learn software concepts.
    10 Use abstract data types to help solve programming problems

    The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
    The course is designed to develop the following Elements of Competency: 1.1   1.2   1.3   1.4   1.5   1.6   2.1   2.2   3.1   3.2   3.6   

    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    1, 5, 6
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • Able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
  • Learning Resources
    Required Resources
    The recommended reference text for this course is: Problem Solving with C++, Walter Savitch
    Recommended Resources
    Students who have Java as a programming language and are entering this course are strongly encouraged to make use of the simple on-line resource that will be made available on the course website, closer to the start of term.
    Online Learning
    In this course, we use the myUni online Learning Management System. The link for the course is at
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The course has two contact activities: lectures and practicals. Each of these activities will provide you with the resources necessary to understand the course material.

    Lectures will present information and provide an opportunity for the introduction and discussion of programming, algorithmic and other material. You should expect to attend all of these and participate in small group work. 

    Practicals are an in-lab activity session where you will work on the weekly programming tasks in C++, while receiving feedback from practical supervisors who are stationed around the lab area. You will need to discuss your work with the supervisors and other students to ensure that you have understood everything. Carrying out the practical tasks is very important to be able to successfully complete the practical examinations.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    You are expected to allocate 5 hours per week for lectures, approximately 5 hours per week for practicals (as a minimum). On average, you should require no more than 12 hours per week for this course.
    Learning Activities Summary
    The weekly pattern is three one-hour lectures and a two-hour practical session, with a tutorial every fortnight. The outline course content is:

    Week 1
    Review of fundamental C/C++ programming techniques, pointer arithmetic and function pointers, memory errors and core dumps

    Week 2
    Abstract data types and class hierarchies

    Week 3
    Inheritance, friends, and overloading

    Week 4
    Using classes, OO Design principles, testing and design

    Week 5
    Principles of software re-use and maintenance, recursion

    Week 6
    Ethics, polymorphism, using ADTs to produce usable structures

    Week 7
    Introduction to complexity analysis, upper and lower complexity bounds, best-case and worst-case, big O, little o, omega and theta

    Week 8
    Complexity analysis, searching and sorting Algorithms

    Week 9
    Recursive complexity
, linked lists and stacks

    Week 10
    Queues, other linked list based data structures

    Week 11
    Trees, algorithmic strategies

    Week 12
    Problem solving, programming paradigms, introduction to type systems

    The course is structured to take you from an introductory knowledge of C++ to a higher level, as well as addressing some key areas of computer programming and algorithm design.

    The summary of the areas covered in this course are:

    Review and development of previous knowledge of C++
    Fundamental data structures
    Object-oriented Programming
    Fundamental Computing Algorithms
    Basic Algorithmic Analysis
    Algorithmic Strategies
    Overview of programming languages
    Software Engineering
    Software Evolution
    Professional Skills Development
    Specific Course Requirements
    There are no specific course requirements,.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Weighting (%) Individual/ Group Formative/ Summative
    Due (week)*
    Hurdle criteria Learning outcomes
    Written Examination 60 Individual Summative Week 13 Min 40% 1. 2. 3. 4. 5. 6. 8. 10.
    Practical Examinations 40 Individual Summative Week 3,6,12 1. 4. 10.
    Total 100
    * The specific due date for each assessment task will be available on MyUni.
    This assessment breakdown is registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s):
    This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.

    Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.

    Practical examination 2 (week 6) and practical examination 3 (week 12) will be carried out online. Invigilation will be finalised over the
    coming weeks and communicated at a later stage.
    Assessment Related Requirements
    Students must achieve an overall passing mark and least 40% in the main exam. 

    Assessment Detail

    Assignments must be submitted through electronic means that will be clearly identified on the assignment rubric.

    Extensions may be requested in advance for medical or compassionate reasons but (1) all requests must be accompanied by documentation, (2) extensions awarded will be in proportion to the time lost that is supported by documentation, (3) extensions are almost never granted on the final day unless the issue is both severe and unforeseen, and (4) extensions are never granted because you have been busy, have managed your time poorly or are overloaded in other courses.

    Any other work submitted will be marked and returned to you within 10 working days. If your work is considered to not be a sufficient attempt, you may be asked to resubmit the work. If we can identify that you are trending towards overall insufficient progress (and at risk of triggering the minimum performance threshold) then we may contact you to make you explicitly aware of this risk, however, you should be tracking your own progress and making your best attempt at every piece of work, rather than aiming to scrape by.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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